DOI: 10.1007/s11069-020-04242-y
论文题名: Using mixing model to interpret the water sources and ratios in an under-sea mine
作者: Gu H. ; Ni H. ; Ma F. ; Liu G. ; Hui X. ; Cao J.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 104, 期: 2 起始页码: 1705
结束页码: 1722
语种: 英语
中文关键词: Hydrochemistry
; Mixing model
; PCA
; Proportion
; Water inrush
; Water sources
英文关键词: concentration (composition)
; ground conditions
; hydrochemistry
; infiltration
; ion exchange
; ionic composition
; model test
; precision
; principal component analysis
; reconstruction
; submarine mining
英文摘要: Identification of water sources is a key issue of water inrush. This study applied a mixing model based on hydrochemical data to identify water sources and proportions. This study highlighted (1) the importance of model scale and reaction evaluation before using the mixing model, (2) a newly proposed criterion based on eigenvalue analysis to identify the number of end-members, and (3) linear mixing model based on PCA (principal component analysis). 2.5 km2 area was an appropriate scale to mixing model because tectonics and lithology were simple. Ion activity, ion exchange, and cycle time of water were evaluated, indicating that groundwater components were dominated by the mixing process. Tracers, such as K, Na, Ca, Mg, Cl, SO4, δ18O, δD, EC, TH, and TDS, were used as tracers in the mixing model. Five end-members (representing seawater, Quaternary water, freshwater, Ca-rich water, and Mg-rich water) were identified based on eigenvalue analysis and hydrochemical evolution analysis. A linear mixing algorithm was programmed using Matlab to compute the ratio of each end-member. The results showed that seawater was the dominated water sources (70% at most) threatening the mining operations, especially at the deep levels. Quaternary water mainly recharged the middle level and made up 50% at − 420 m level. Freshwater recharged the shallow level and made up to 40% at − 150 m level. Ca-rich water and Mg-rich water decreased with time. Finally, cross test and extension test of this method showed a high precision in reconstructing ion concentrations, low sensitivity to noise data, and highly extendible to future data. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168508
Appears in Collections: 气候变化与战略
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作者单位: Chengdu Center, China Geological Survey, Chegndu, Sichuan 610081, China; China Merchants Chongqing Communications Research and Design Institute Co., Ltd, Chongqing, China; Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China; Nanjing Center, China Geological Survey, Nanjing, Jiangsu 210016, China; Xian Center, China Geological Survey, Xian, Shanxi 710054, China; Beijing Jingtou Urban Utility Tunnel Investment Co., Ltd, Beijing, China; Beijing Infrastructure Investment Co., Ltd, Beijing, China
Recommended Citation:
Gu H.,Ni H.,Ma F.,et al. Using mixing model to interpret the water sources and ratios in an under-sea mine[J]. Natural Hazards,2020-01-01,104(2)